{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T14:48:12Z","timestamp":1786546092187,"version":"build-2736575974"},"reference-count":24,"publisher":"Sociedade Brasileira de Cardiologia","issue":"7","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"am","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Arq. Bras. Cardiol."],"abstract":"<jats:p>RESUMO As doen\u00e7as cardiovasculares s\u00e3o a principal causa de mortalidade no mundo, destacando a necessidade de estrat\u00e9gias eficazes de predi\u00e7\u00e3o de risco e detec\u00e7\u00e3o precoce. Embora o eletrocardiograma (ECG) seja um exame amplamente dispon\u00edvel e de baixo custo, sua interpreta\u00e7\u00e3o tradicional \u00e9 limitada pela subjetividade. A intelig\u00eancia artificial (IA) surgiu como uma abordagem promissora, capaz de extrair informa\u00e7\u00f5es progn\u00f3sticas ocultas dos sinais de ECG. Esta revis\u00e3o sistem\u00e1tica teve como objetivo avaliar estudos originais que aplicaram t\u00e9cnicas de IA a ECGs para predi\u00e7\u00e3o de risco cardiovascular e mortalidade. Foram inclu\u00eddos estudos originais que utilizaram sinais de ECG como \u00fanica vari\u00e1vel de entrada para modelos de IA, com foco em desfechos de risco cardiovascular. Uma busca sistem\u00e1tica foi realizada em diferentes bases de dados, e os dados fora msintetizados de forma narrativa. Onze estudos foram inclu\u00eddos, predominantemente coortes retrospectivas que aplicaram redes neurais convolucionais (CNNs) para prever risco cardiovascular ou mortalidade. As amostras eram majoritariamente compostas por popula\u00e7\u00f5es adultas de pa\u00edses de alta renda. Os desfechos prim\u00e1rios inclu\u00edram mortalidade por todas as causas, morte cardiovascular e eventos cardiovasculares adversos maiores (MACE). Os valores de AUROC variaram de 0,63 a 0,961 nos conjuntos de treinamento, com alguns modelos superando escores tradicionais de risco. Os modelos de IA\u2011ECG demonstraram potencial para detectar doen\u00e7a subcl\u00ednica, permitindo estratifica\u00e7\u00e3o precoce de risco mesmo em ECGs normais. No entanto, persistem desafios relacionados \u00e0 diversidade populacional, interpretabilidade dos modelos e valida\u00e7\u00e3o prospectiva. A aplica\u00e7\u00e3o de IA \u00e0 an\u00e1lise de ECG representa um avan\u00e7o promissor na avalia\u00e7\u00e3o personalizada do risco cardiovascular. Contudo, mais pesquisas s\u00e3o necess\u00e1rias para garantir a seguran\u00e7a, a efic\u00e1cia e a integra\u00e7\u00e3o cl\u00ednica equitativa dessas tecnologias.<\/jats:p>","DOI":"10.36660\/abc.20250790","type":"journal-article","created":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T13:51:24Z","timestamp":1786542684000},"source":"Crossref","is-referenced-by-count":0,"title":["Intelig\u00eancia Artificial Aplicada \u00e0 Avalia\u00e7\u00e3o de Risco Cardiovascular Baseada em Eletrocardiograma: Uma Revis\u00e3o Sistem\u00e1tica"],"prefix":"10.36660","volume":"123","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-8808-1934","authenticated-orcid":false,"given":"Maria Clara Mantoan","family":"Pinheiro","sequence":"first","affiliation":[{"name":"Universidade Federal de Minas Gerais,  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